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for the interview presentation. The interviews are performed by a panel of UCMR and UPSC researchers. The date of the final interview is 6-7 October 2025. Learn more about life as an ‘EC’ postdoc
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postdoctoral position in data analysis, where you will apply machine learning techniques to understand how resistance genes spread and to help detect infections caused by resistant bacteria. The position is part
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foundational and applied topics in computer vision and machine learning, with particular strengths in inverse problems, generative models, and geometric deep learning. We work across diverse application areas
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with modern machine learning and AI technologies to effectively address large-scale problems. About the research project We are seeking a highly motivated Postdoc to join our group in developing
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application! Work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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-ray Science. AMBER is funded by the EU Marie Skłodowska-Curie (MSCA) COFUND scheme. Around 20 postdocs will be recruited in the fourth call 2025, with each fellowship lasting 36 months. AMBER has six
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great advantage: Forest and wood production processes Wood construction Furniture manufacturing Wood material science Machine learning Process simulation and optimisation The postdoctoral fellow is part
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The postdoc fellow will conduct research in the intersection of AI/Machine Learning and Software Technology. The advertised position will be placed in the DISTA research group (https://lnu.se/en/dista
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magnetoelectric coupling, particularly those related to chiral magnetism. Who we are looking for We seek candidates with the following qualifications: To qualify for the position of postdoc, you must hold a